<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The escalation of code plagiarism in computer science education has necessitated the development of more sophisticated detection methods, particularly for binary files which pose a unique challenge. This study introduces a novel approach to plagiarism detection through binary decomposition, which decompiles binary files back into high-level code to reveal similarities that may be hidden at the binary level. The methodology is crucial for scenarios where students submit compiled programs, enabling the application of traditional code similarity analysis methods to detect instances of plagiarism. Statistical data on code similarity among student submissions in a C programming course are presented, highlighting the urgent need for robust detection strategies. This paper explores the ethical implications of plagiarism, the technical challenges of binary file analysis, and the potential for applying this technique across various programming languages and educational contexts.</p>
</abstract>

The escalation of code plagiarism in computer science education has necessitated the development of more sophisticated detection methods, particularly for binary files which pose a unique challenge. This study introduces a novel approach to plagiarism detection through binary decomposition, which decompiles binary files back into high-level code to reveal similarities that may be hidden at the binary level. The methodology is crucial for scenarios where students submit compiled programs, enabling the application of traditional code similarity analysis methods to detect instances of plagiarism. Statistical data on code similarity among student submissions in a C programming course are presented, highlighting the urgent need for robust detection strategies. This paper explores the ethical implications of plagiarism, the technical challenges of binary file analysis, and the potential for applying this technique across various programming languages and educational contexts.

Code Clones: A Novel Approach to Detecting Plagiarism in Binary Decomposition of C Programs

Department of Computers and Informatics, Faculty of Electrical Engineering and Informatics

Acta Electrotechnica et Informatica

This work is licensed under the Creative Commons Attribution 4.0 International License.

The escalation of code plagiarism in computer science education has necessitated the development of more sophisticated detection methods, particularly for...

Code Clones: A Novel Approach to Detecting Plagiarism in Binary Decomposition of C Programs

Online veröffentlicht: 15. Juli 2024

Seitenbereich: 13 - 18

Eingereicht: 15. Jan. 2024

Akzeptiert: 26. Juni 2024

DOI: https://doi.org/10.2478/aei-2024-0006

Schlüsselwörter
Plagiarism Detection, Binary Decomposition, Computer Science Education, Algorithmic Analysis, Pattern Recognition, Academic Integrity

© 2024 Marek Horváth et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Code Clones: A Novel Approach to Detecting Plagiarism in Binary Decomposition of C Programs

Online veröffentlicht: 15. Juli 2024

Seitenbereich: 13 - 18

Eingereicht: 15. Jan. 2024

Akzeptiert: 26. Juni 2024

DOI: https://doi.org/10.2478/aei-2024-0006

SchlüsselwörterPlagiarism Detection, Binary Decomposition, Computer Science Education, Algorithmic Analysis, Pattern Recognition, Academic Integrity

© 2024 Marek Horváth et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Plagiarism Detection, Binary Decomposition, Computer Science Education, Algorithmic Analysis, Pattern Recognition, Academic Integrity